1. Field of the Invention
The present invention relates to systems for determining consumer preferences. More specifically, the invention relates to systems for determining consumer preference information relating to product attributes and to product attribute levels.
2. Description of the Related Art
During the design of a product, a manufacturer must choose from among several available product features, or attributes, to include in the product. Some attributes may be optional while others may be required. In the case of a television set, “Chassis color” is an attribute that must be included and “Picture-in-picture” is an optional attribute. For each included attribute, a manufacturer must also choose an attribute level to associate with the attribute. Attribute levels that may be associated with the attribute “Chassis color” include “black”, “white”, “blue”, etc.
Trade-off analysis techniques attempt to determine consumers' preferences for particular product attributes and attribute levels in order to identify ideal product configurations. A consumer, in this regard, is any entity to which a product may be offered. Such consumers include individuals, businesses, and purchasing managers, and a product may include a good and/or service.
For example, trade-off analysis techniques allow a manufacturer to compare the attractiveness of a Sony television priced at $599 with that of a Magnavox television priced at $399. Such a comparison is possible because the techniques associate a particular numerical value with a consumer's preference for each attribute and attribute level. Accordingly, the relative attractiveness of differences or changes in attributes with respect to differences or changes in any other attribute can be determined simply by comparing the appropriate associated numerical values. For example, the attractiveness of a price change from $599 to $399 may be compared with the attractiveness of a brand change from Magnavox to Sony. Therefore, by using consumer preference information, a manufacturer is more likely to choose product configurations as well as production amounts and prices for each product configuration that improve sales objectives such as overall profit, consumer satisfaction and consumer loyalty.
As described in the Background of commonly-assigned co-pending U.S. patent application Ser. No. 09/754,612, entitled SYSTEM TO QUANTIFY CONSUMER PREFERENCES, which is incorporated by reference herein for all purposes, conventional trade-off analysis techniques include conjoint, discrete choice, self-explicated, and hybrid techniques. Each of these techniques may be used to produce consumer preference information. However, these techniques often fail to produce a full complement of consumer preference information associated with a particular consumer. In other instances, the produced consumer preference information unsatisfactorily reflects the particular consumer's preferences. As a result, it is difficult to use conventionally-collected consumer preference information to accurately determine, for example, an amount of change in a consumer's preference for a product that would result from a change in a particular attribute or a particular attribute level of the product.
In an attempt to address the foregoing, some conventional systems apply stabilization algorithms to the produced consumer preference information. The stabilization algorithms are intended to improve the predictive precision and completeness of the consumer preference information. In one conventional system, the Adaptive Conjoint Analysis/Hierarchical Bayes module sold by Sawtooth Software, Inc., consumer preference information of other consumers is used to stabilize consumer preference information of a subject consumer. However, these conventional stabilization algorithms are also not seen to produce sufficiently predictive or complete consumer preference information.
In view of the foregoing, what is needed is a system to determine consumer preference information that provides greater predictive precision than that produced by conventional systems.